Stats4Grads: Study of Joint Type-II Censoring in Heterogeneous Populations
1 June 2016 13:00 in CM105
Time to event, or survival, data is common in the biological and medical sciences with typical examples being time to death and time to recurrence of a tumour. In practice, survival data is typically subject to censoring with incomplete observation of some failure times due to drop-out, intermittent follow-up and finite study duration.
Here, we consider the analysis of time to event data from two populations undergoing life-testing, mainly under a joint Type-II censoring scheme for heterogeneous situations. We consider a mixture model formulation and maximum likelihood estimation using the EM algorithm and conduct a simulation to study the effect of the form of censoring scheme on parameter estimation and study duration.
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